Radiotherapy is used to treat cancers and other ailments in mammalian (e.g., human and animal) tissue. One such radiotherapy technique is a Gamma Knife, by which a patient is irradiated by a large number of low-intensity gamma rays that converge with high intensity and high precision at a target (e.g., a tumor). In another embodiment, radiotherapy is provided using a linear accelerator, whereby a tumor is irradiated by high-energy particles (e.g., electrons, protons, photons, ions, and the like). The placement and dose of the radiation beam must be accurately controlled to ensure the tumor receives the prescribed radiation, and the placement of the beam should be such as to minimize damage to the surrounding healthy tissue, often called the organ(s) at risk (OARS). Furthermore, in yet another embodiment, radiotherapy can be provided by brachytherapy, which allows high doses of radiation to be placed internally at specific areas of the body.
When using an external radiation therapy, the radiation beam may be shaped to match a shape of the tumor, such as by using a multileaf collimator (e.g., multileaf collimator includes multiple tungsten leaves that may move independently of one another to create customized radiation beam shapes). (Radiation is termed “prescribed” because a physician orders a predefined amount of radiation to the tumor and surrounding organs similar to a prescription for medicine).
Traditionally, for each patient, a radiation therapy treatment plan (“treatment plan”) may be created using an optimization technique based on clinical and dosimetric objectives and constraints (e.g., the maximum, minimum, and mean doses of radiation to the tumor and critical organs). The treatment planning procedure may include using a three-dimensional image of the patient to identify a target region (e.g., the tumor) and to identify critical organs near the tumor. Each structure (e.g., a target, a tumor, an OAR, etc.) can be discretized into a finite number of volume cubes, known as voxels. Creation of a treatment plan can be a time consuming process where a planner tries to comply with various treatment objectives or constraints (e.g., dose volume histogram (DVH) objectives), taking into account their individual importance (e.g., weighting) in order to produce a treatment plan which is clinically acceptable. This task can be a time-consuming trial-and-error process that is complicated by the various organs at risk (OARs), because as the number of OARs increases (e.g., up to thirteen or more for a head-and-neck treatment), so does the complexity of the process. OARs distant from a tumor may be easily spared from radiation, while OARs close to or overlapping a target tumor may be difficult to spare.
Computed Tomography (CT) imaging traditionally serves as the primary source of image data for treatment planning for radiation therapy. CT images offer accurate representation of patient geometry, and CT values can be directly converted to electron densities (e.g., Hounsfield units) for radiation dose calculation. However, using CT causes the patient to be exposed to additional radiation dosage. In addition to CT images, magnetic resonance imaging (MRI) scans can be used in radiation therapy due to their superior soft-tissue contrast, as compared to CT images. MRI is free of ionizing radiation and can be used to capture functional information of the human body, such as tissue metabolism and functionality.
Imaging systems such as computed tomography (CT), ultrasound, fluoroscopy, and magnetic resonance imaging (MRI) may be used to determine the location of a target and to track the target (e.g., an organ, a tumor, and the like). MRI can be used because it provides excellent soft tissue contrast without using ionizing radiation as used by CT. An example of a radiotherapy treatment system integrated with an imaging system may include an MRI-Linac, which may use three-dimensional (3D) images of a target (e.g., a tumor). The MRI apparatus of the MRI-Linac may provide a plurality of images that corresponds to a partial map of hydrogen nuclei in tissues of the patient. The patient images may be acquired in a one-dimensional (1D) line, a two-dimensional (2D) plane, or in a 3D volume. Because organs and tumors move within a patient's body, fast and accurate 3D localization of the target is important. For instance, a target organ or tumor may move because of various types of motion (e.g., respiratory, cardiac, peristalsis or other types of patient motion).
Treatment outcomes depend upon many factors. Those factors include accurate target contouring, correct dose calculation and delivery, precise radiation beam collimation, and accurate patient positioning, which includes precise localization of a moving tumor. Typically both patient setup and intrafraction monitoring for radiation therapy treatment uses image localization using bony landmarks, fiducial markers, or soft tissue.
Images of the patient's anatomy taken at different times may be analyzed to determine the movement of this anatomy over the intervening period. This may be done between images of the same modality, or between images of different modalities. A human operator monitoring the patient's position has problems of inattention, and is not able to provide correction in real time. Therefore it is useful to apply image analysis methods to localize the anatomy, and adjust the treatment (e.g. linac gating, or MLC movement), in real time. However, most localization algorithms do not provide information whether the results of localization are adequate for determining target motion. Therefore, what is needed is a method and system that can quickly, efficiently, and automatically determine in real-time the quality of the localization of a target in an image, which can provide information as to whether the treatment decision (to adjust or not) can be considered reliable.